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pythonpandasdate-rangereindex

Re-index dataframe by new range of dates

I have a data frame containing a number of observations:

date         colour     orders
2014-10-20   red        7
2014-10-21   red        10
2014-10-20   yellow     3

I would like to re-index the data frame and standardise the dates.

date         colour     orders
2014-10-20   red        7
2014-10-21   red        10
2014-10-22   red        NaN
2014-10-20   yellow     3
2014-10-21   yellow     NaN
2014-10-22   yellow     NaN

I though to order the data frame by colour and date, and then try to re-index it.

index = pd.date_range('20/10/2014', '22/10/2014')
test_df = df.sort(['colour', 'date'], ascending=(True, True))
ts = test_df.reindex(index)
ts

But it returns a new data frame with the right index but all NaN values.

date         colour     orders
2014-10-20   NaN        NaN
2014-10-21   NaN        NaN
2014-10-22   NaN        NaN
Solution

  • Starting from your exampe dataframe:

    In [51]: df
Out[51]:
        date  colour  orders
0 2014-10-20     red       7
1 2014-10-21     red      10
2 2014-10-20  yellow       3

    If you want to reindex on both 'date' and 'colour', one possibility is to set both as the index (a multi-index):

    In [52]: df = df.set_index(['date', 'colour'])

In [53]: df
Out[53]:
                   orders
date       colour
2014-10-20 red          7
2014-10-21 red         10
2014-10-20 yellow       3

    You can now reindex this dataframe, after you constructed to desired index:

    In [54]: index = pd.date_range('20/10/2014', '22/10/2014')

In [55]: multi_index = pd.MultiIndex.from_product([index, ['red', 'yellow']])

In [56]: df.reindex(multi_index)
Out[56]:
                   orders
2014-10-20 red          7
           yellow       3
2014-10-21 red         10
           yellow     NaN
2014-10-22 red        NaN
           yellow     NaN

    To have the same output as your example output, the index should be sorted in the second level (level=1 as it is 0-based):

    In [60]: df2 = df.reindex(multi_index)

In [64]: df2.sortlevel(level=1)
Out[64]:
                   orders
2014-10-20 red          7
2014-10-21 red         10
2014-10-22 red        NaN
2014-10-20 yellow       3
2014-10-21 yellow     NaN
2014-10-22 yellow     NaN

    A possible way to generate the multi-index automatically would be (with your original frame):

    pd.MultiIndex.from_product([pd.date_range(df['date'].min(), df['date'].max(), freq='D'), 
                            df['colour'].unique()])

    Another way would be to use resample for each group of colors:

    In [77]: df = df.set_index('date')

In [78]: df.groupby('colour').resample('D')

    This is simpler, but this does not give you the full range of dates for each colour, only the range of dates that is available for that colour group.